[BioC] Data set for comparing statistical tests
James W. MacDonald
jmacdon at uw.edu
Fri Aug 31 21:02:04 CEST 2012
Hi Jorge,
pData(phenoData(SpikeIn133))
Best,
Jim
On 8/31/2012 2:12 PM, Jorge Miró wrote:
> Hi again,
>
> I have been trying to understand how I should go on with the spike in
> data but in vain.
> Here are the commands I used:
>
>
> ************ Code *************************
>> library(SpikeIn)
>> data(SpikeIn133)
> #Checked phenoData as suggested....
>> phenoData(SpikeIn133)
> An object of class "AnnotatedDataFrame"
> sampleNames: 12_13_02_U133A_Mer_Latin_Square_Expt1_R1
> 12_13_02_U133A_Mer_Latin_Square_Expt2_R1 ...
> 12_13_02_U133A_Mer_Latin_Square_Expt14_R3 (42 total)
> varLabels: 203508_at 204563_at ... AFFX-ThrX-3_at (42 total)
> varMetadata: labelDescription
>
> # ... but I could not see the concentrations for the samples. Is it
> something else I should do? I tryid with pData too and I could not
> find any information about the samples concentration.
>
> *************************** End of code ******************'
> I guess the SpikeIn133 is a file with raw intensities so I shoud apply
> rma on it and then use eg limma to test for differential expression of
> the genes. Am I right?
>
> I read the manual for SpikeIn but I can't see anything about the
> concentrations for each sample in the data set
> (http://www.bioconductor.org/packages/2.10/data/experiment/manuals/SpikeIn/man/SpikeIn.pdf)
>
>
> Best regards
> Jorge
>
> On Fri, Aug 31, 2012 at 12:01 PM, Benilton Carvalho
> <beniltoncarvalho at gmail.com> wrote:
>> check the SpikeIn package... in particular the phenoData slot for the
>> datasets available. b
>>
>> On 31 August 2012 10:58, Jorge Miró<jorgma86 at gmail.com> wrote:
>>> Hi everybody,
>>>
>>> I need to compare Student's t-test and the test implemented in the
>>> limma package. Does any body has an idea of how I should do?
>>>
>>> I guess I need a data set with already known differentially expressed
>>> genes (maybe this can be done by specially designing the probesets in
>>> the used arrays?) and then compare the results of a t-tests and limma
>>> test with the expected differentially expressed genes. Where can I get
>>> such a data set?
>>>
>>> Sorry if the question is a bit stupid but I'm new to microarray
>>> analysis and statistics... By the way, should this kind of questions
>>> be posted here or should I use another forum?
>>>
>>>
>>>
>>> Best regards
>>> Jorge
>>>
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--
James W. MacDonald, M.S.
Biostatistician
University of Washington
Environmental and Occupational Health Sciences
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Seattle WA 98105-6099
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